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Objective: The most relevant source of signal contamination in the cardiacelectrophysiology (EP) laboratory is the ubiquitous powerline interference(PLI). To reduce this perturbation, algorithms including common fixed bandwidthand adaptive notch filters have been proposed. Although such methods haveproven to add artificial fractionation to intra atrial electrograms (EGMs),they are still frequently used. However, such morphological alteration canconceal the accurate interpretation of EGMs, specially to evaluate themechanisms supporting atrial fibrillation (AF), which is the most commoncardiac arrhythmia. Given the clinical relevance of AF, a novel algorithm aimedat reducing PLI on highly contaminated bipolar EGMs and, simultaneously,preserving their morphology is proposed. Approach: The method is based on thewavelet shrinkage and has been validated through customized indices on a set ofsynthesized EGMs to accurately quantify the achieved level of PLI reduction andsignal morphology alteration. Visual validation of the algorithms performancehas also been included for some real EGM excerpts. Main results: The method hasoutperformed common filtering-based and wavelet based strategies in theanalyzed scenario. Moreover, it possesses advantages such as insensitivity toamplitude and frequency variations in the PLI, and the capability of jointremoval of several interferences. Significance: The use of this algorithm inroutine cardiac EP studies may enable improved and truthful evaluation of AFmechanisms.

The Stationary Wavelet Transform as an Efficient Reductor of Powerline Interference for Atrial Bipolar Electrograms in Cardiac Electrophysiology